- Sponsor:
- sighpc
This workshop aims to bring together leading researchers and software designers at the forefront of the application of high-level directives to program accelerator-based architectures. Using directives improve productivity, and program portability with minimal changes to the applications while achieving good power-efficiency and performance. HPC researchers and programmers (including Energy, Climate, Oil & Gas, Computational Chemistry, and Machine Learning) wishing to tap into the performance benefits of commodity accelerators are starting to use directives to program accelerators including OpenACC, OpenMP and other similar programming interfaces vigorously to tap into commodity accelerators and speed up applications.
The goal of this workshop is to bring together users, vendors, and tools providers to share their knowledge and experiences to program heterogeneous systems using directive-based programming interfaces such as OpenACC, OpenMP, etc to achieve good performance. This year's workshop will also emphasize in the future direction of accelerator programming using directives and how we can address better the user and tools-ecosystem needs.
Proceeding Downloads
OpenARC: extensible OpenACC compiler framework for directive-based accelerator programming study
Directive-based, accelerator programming models such as OpenACC have arisen as an alternative solution to program emerging Scalable Heterogeneous Computing (SHC) platforms. However, the increased complexity in the SHC systems incurs several challenges ...
An OpenACC extension for data layout transformation
OpenACC is gaining momentum as an implicit and portable interface in porting legacy CPU-based applications to heterogeneous, highly parallel computational environment involving many-core accelerators such as GPUs and Intel Xeon Phi. OpenACC provides a ...
Achieving portability and performance through OpenACC
OpenACC is a directive-based programming model designed to allow easy access to emerging advanced architecture systems for existing production codes based on Fortran, C and C++. It also provides an approach to coding contemporary technologies without ...
XcalableACC: extension of XcalableMP PGAS language using OpenACC for accelerator clusters
- Masahiro Nakao,
- Hitoshi Murai,
- Takenori Shimosaka,
- Akihiro Tabuchi,
- Toshihiro Hanawa,
- Yuetsu Kodama,
- Taisuke Bokut,
- Mitsuhisa Sato
The present paper introduces the XcalableACC (XACC) programming model, which is a hybrid model of the XcalableMP (XMP) Partitioned Global Address Space (PGAS) language and OpenACC. XACC defines directives that enable programmers to mix XMP and OpenACC ...
Accelerating Kirchhoff migration on GPU using directives
Accelerators offer the potential to significantly improve the performance of scientific applications when offloading compute intensive portions of programs to the accelerators. However, effectively tapping their full potential is difficult owing to the ...
Accelerating a C++ CFD code with OpenACC
Todays HPC systems are increasingly utilizing accelerators to lower time to solution for their users and reduce power consumption. To utilize the higher performance and energy efficiency of these accelerators, application developers need to rewrite at ...
Directive-based parallelization of the NIM weather model for GPUs
The NIM is a performance-portable model that runs on CPU, GPU and MIC architectures with a single source code. The single source plus efficient code design allows application scientists to maintain the Fortran code, while computer scientists optimize ...
Index Terms
- Proceedings of the First Workshop on Accelerator Programming using Directives
Recommendations
Towards achieving performance portability using directives for accelerators
WACCPD '16: Proceedings of the Third International Workshop on Accelerator Programming Using DirectivesIn this paper we explore the performance portability of directives provided by OpenMP 4 and OpenACC to program various types of node architectures with attached accelerators, both self-hosted multicore and offload multicore/GPU. Our goal is to examine ...
Acceptance Rates
| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| WACCPD '15 | 14 | 7 | 50% |
| Overall | 14 | 7 | 50% |